In an increasingly interconnected world, mobile and wearable devices, through short range communication interfaces and sensors, become needful tools for collecting and disseminating information in high population density environments. In this context MCS, leveraging people’s roaming and their devices’ resources, raised the citizen from mere walk-on part to active participant in the knowledge building and data dissemination process. At the same time, MEC architecture has recently enhanced the two-layer cloud-device architectural model easing the exchange of information and shifting most computational cost from devices towards middle-layer proxies, namely, network edges. We introduce Human-driven Edge Computing, a new model which melts together the power of MEC platform and the large-scale sensing of MCS in order to realize a better data spreading and environmental coverage in smart cities. In addition, will be briefly discussed the main sociological aspects related to human behavior and how they can actually influence the exchange of data in large-scale sensor networks.

Enhancing Mobile Edge Computing Architecture with Human-driven Edge Computing Model

Dimitri Belli;Stefano Chessa;
2018

Abstract

In an increasingly interconnected world, mobile and wearable devices, through short range communication interfaces and sensors, become needful tools for collecting and disseminating information in high population density environments. In this context MCS, leveraging people’s roaming and their devices’ resources, raised the citizen from mere walk-on part to active participant in the knowledge building and data dissemination process. At the same time, MEC architecture has recently enhanced the two-layer cloud-device architectural model easing the exchange of information and shifting most computational cost from devices towards middle-layer proxies, namely, network edges. We introduce Human-driven Edge Computing, a new model which melts together the power of MEC platform and the large-scale sensing of MCS in order to realize a better data spreading and environmental coverage in smart cities. In addition, will be briefly discussed the main sociological aspects related to human behavior and how they can actually influence the exchange of data in large-scale sensor networks.
978-1-5386-6844-3
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/939939
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